Bibliographic record
Abstract
Abstract This paper locates acute and ongoing crises of coloniality and ecology within struggles over circulation that are anchored in infrastructure. If infrastructure organises movement—including its constraint in carceral forms—then it is also a linchpin for materialising distinct regimes of motion (Nail 2020a; Marx in Motion: A New Materialist Marxism). A regime of motion may be inherently violent, underpinning reproduction for some by interrupting it for others. It may be assembled to sustain imperialism's “expanded reproduction”, curtailing or crushing the plethora of alternative forms to produce premature death. Yet, a focus on struggles over the organisation of motion and, specifically, the contestation of imperial infrastructure, allows the practical assembly of otherwise and alimentary forms to become apprehensible. Journeying through logistics systems that both craft and cut through colonial ecologies, this essay tracks haunted rails, moves across racial and national borders of land, labour, livestock, and the human, and into the intimate space of the singular microbiome. Holding seemingly disparate sites of crisis together, it attends to practices of survivance of those who refuse the violently sculpted borders of life and death. I ask, what infrastructural inheritances usher in this apocalyptic era and how might an immanent politics of care and collaboration—a palliative politics—orient us towards other paths?
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.085 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.004 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".